NLoS error suppression algorithm based on two-step Kalman filtering
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摘要: 针对超宽带(ultra wide band，UWB)定位中影响定位精度的非视距(non line of sight, NLoS)传播误差问题，提出了一种基于Kalman滤波的NLoS误差二次消除方法. 该方法利用NLoS误差与测量误差之间的相互独立性，借助Kalman滤波将NLoS误差从总误差中单独分离出来，对其进行实时估计，并将该NLoS误差估计值作为NLoS误差辨别及测距值修正的依据. 通过Kalman滤波对到达时间(time of arrival, TOA)测距值进行二次估计、鉴别及修正以提高TOA测距精度，从而实现室内复杂环境下的UWB精准实时定位. 仿真实验结果表明：该方法不仅能够对NLoS误差实现良好的跟踪估计，对视距(line of sight, LoS)/NLoS环境转变也具有较强的灵敏感知能力，同时NLoS误差测距值在应用该方法后的定位性能逼近于LoS环境下的理想状态.Abstract: In order to solve the problem of non-line-of-sight propagation error which affects the positioning accuracy in ultra wide band (UWB) positioning, a secondary elimination method of non line of sight (NLoS) error based on kalman filtering is proposed. This method makes use of the mutual independence between the NLoS error and the measurement error, separates the NLoS error from the total error with the help of Kalman filter, estimates it in real time, and uses the estimated value of the NLoS error as the basis for NLoS error identification and distance measurement correction. Time of arrival (TOA) ranging accuracy is improved by secondary estimation, discrimination and correction of TOA ranging value through Kalman filtering, thus accurate real-time positioning of UWB in indoor complex environment is realized. The simulation results show that this method can not only track and estimate NLoS errors, but also has strong sensitivity to the transition of line-of-sight (LoS)/NLoS environment. The location performance of NLoS error measurements after applying this method is close to the ideal state in LoS environment.
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表 1 不同环境下的模型参数
无线信道环境 $ {T_1}/{\text{μs}} $ $\varepsilon $ ${\sigma _\xi }/{\text{dB}}$ 繁华市区 0.90 0.5 4 一般市区 0.40 0.5 4 郊区 0.20 0.5 4 远郊 0.10 0.5 4 山区 0.45 1.0 6 
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